code: def __init__(self, in_channels, num_fiducial):
      super(GridGenerator, self).__init__()
      self.eps = 1e-6
      self.F = num_fiducial
  
      name = "ex_fc"
      initializer = nn.initializer.Constant(value=0.0)
      param_attr = ParamAttr(
          learning_rate=0.0, initializer=initializer, name=name + "_w"
      )
      bias_attr = ParamAttr(
          learning_rate=0.0, initializer=initializer, name=name + "_b"
      )
      self.fc = nn.Linear(
          in_channels,
          6,
          weight_attr=param_attr,
          bias_attr=bias_attr,
          name=name,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  from paddle import nn, ParamAttr
  from paddle.nn import functional
  import numpy
label_desc: Use image node_id 1 to create a new GridGenerator object from inherited base classes: nn with example: obj = GridGenerator(in_channels, num_fiducial)